Powerlytics and Attom

Powerlytics Data Helps Mortgage Lenders Understand Foreclosure Risk

Published 16th Apr 2024
News and EventsPredictive AnalyticsRisk
Back to blog

Unveiling ATTOM’s Propensity to Default Score: Navigating Mortgage Foreclosure Risks

With February home foreclosure activity up 8% vs. a year ago, understanding a borrower’s willingness and ability to stay current on their mortgage and out of default becomes even more critical for mortgage lenders.

While total foreclosures remain low by historic standards – 2023 saw 357,062 total foreclosure filings or 0.26% of all US housing units vs. the peak year of 2010 which saw over 2.8M foreclosure filings representing 2.23% of all US housing units – the number has more than doubled since 2021 and we continue to see an upward trend.  And certain markets appear to be more problematic with Orlando, FL, Cleveland, OH, Riverside, CA, Philadelphia, PA and Miami, FL well above the national average for February 2024.

With this increase in foreclosures, it becomes even more important for mortgage servicers to gain deeper insights into the borrower’s willingness and ability to stay current on their mortgage.  Along with the value of a home and a homeowner’s equity position, gaining a sense of the likelihood that a given homeowner will go into foreclosure could also be quite helpful.

Using ATTOM’s Propensity to Default Score to Identify Foreclosure Risk

The ATTOM Propensity to Default score provides the insights needed to help mortgage services better understand where there is potential default risk in their portfolios. Supported by an advanced predictive model, which utilizes ATTOM’s extensive foreclosure and mortgage data alongside tax return information from Powerlytics, encompassing over 150 million households across the United States, the Propensity to Default score identifies which properties have the highest and lowest likelihood of going into foreclosure over the next 12 months.

The Propensity to Default score can clearly identify very high-risk properties.  Specifically, the score identifies a top decile (top 10% of properties) that is 5.84 times more likely to go into foreclosure vs. a randomly selected property.

The Propensity to Default score can also identify very low-risk properties.  In fact, the 3 bottom deciles (bottom 30%) are 21 times less likely to go into foreclosure than a randomly selected property and even when this is expanded to the 5 bottom deciles (bottom 50%) the group is still 10 times less likely to go into foreclosure.

Based on these powerful insights of where the foreclosure risk is and is not, mortgage servicers can employ the following portfolio prioritization strategies:

  • Focus more actively on securing payments from mortgage-holders of high-propensity to default properties. For example, mortgage servicing companies may want to use this data to perform early reach out to properties within their portfolios that may have a higher risk of defaulting in the next 12 months.
  • Expend less effort on the lowest propensity to default properties thus potentially realizing cost savings.

 

It is evident that Powerlytics’ accurate, granular, and comprehensive financial data coupled with ATTOM’s rich property insights is a powerful combination in predicting mortgage default propensity and providing mortgage servicers with a powerful tool to better manage their portfolios.

Curious to find out more about Propensity to Default score? As a leading resource for nationwide property data, you can look to ATTOM to help provide extensive real estate data that can potentially help support your business. See how we can help here.